在 Seaborn 组合折线图中添加图例答案

【问题标题】：Add legend in Seaborn combo line bar chart在 Seaborn 组合折线图中添加图例
【发布时间】：2021-11-20 10:04:02
【问题描述】：

我正在尝试向我的 seaborn 条形图 + 折线图添加一个图例，但只收到错误消息“没有找到带有标签的句柄放入图例”。无论我尝试什么。这个怎么办？

from pathlib import Path
import pandas as pd
import seaborn as sns
from matplotlib import pyplot as plt
import matplotlib.dates as mdates
import numpy as np    

dfGroup = pd.DataFrame({
        'Year': [1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920],
        'Total Deaths': [0, 0, 2, 3, 2, 3, 4, 5, 6, 7, 8],
        'Total Affected': [0, 1, 0, 2, 3, 6, 9, 8, 12, 13, 15]
        })
# Add 3-year rolling average
dfGroup['rolling_3years'] = dfGroup['Total Deaths'].rolling(3).mean().shift(0)
dfGroup = dfGroup.fillna(0)

# Make a smooth line from the 3-year rolling average
from scipy.interpolate import make_interp_spline
X_Y_Spline = make_interp_spline(dfGroup['Year'], dfGroup['rolling_3years'])
 
# Returns evenly spaced numbers over a specified interval.
X_ = np.linspace(dfGroup['Year'].min(), dfGroup['Year'].max(), 500)
Y_ = X_Y_Spline(X_)

# Plot the data
a4_dims = (15, 10)
fig, ax1 = plt.subplots(figsize=a4_dims)

ax1 = sns.barplot(x = "Year", y = "Total Deaths",
             data = dfGroup, color='#42b7bd')
ax2 = ax1.twinx()
ax2 = sns.lineplot(X_, Y_, marker='o')

【问题讨论】：

标签： python pandas seaborn

【解决方案1】：

由于 seaborn 的 barplot 使用分类位置，内部编号为 0,1,2,... 的两个图可以绘制在同一个 ax 上。这可以通过重新计算lineplot 的x 值来完成。

要获得图例，应使用label= 关键字。（在twinx 轴上创建图例有点复杂，并且需要创建自定义句柄。）Seaborn 通常会自动创建图例。如果你想改变它的外观，你可以通过自定义参数调用ax1.legend(...)。

下面是一些示例代码：

from pathlib import Path
import pandas as pd
import seaborn as sns
from matplotlib import pyplot as plt
import matplotlib.dates as mdates
import numpy as np

dfGroup = pd.DataFrame({
    'Year': [1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920],
    'Total Deaths': [0, 0, 2, 3, 2, 3, 4, 5, 6, 7, 8],
    'Total Affected': [0, 1, 0, 2, 3, 6, 9, 8, 12, 13, 15]
})
# Add 3-year rolling average
dfGroup['rolling_3years'] = dfGroup['Total Deaths'].rolling(3).mean().shift(0)
dfGroup = dfGroup.fillna(0)

# Make a smooth line from the 3-year rolling average
from scipy.interpolate import make_interp_spline

X_Y_Spline = make_interp_spline(dfGroup['Year'], dfGroup['rolling_3years'])

# Returns evenly spaced numbers over a specified interval.
X_ = np.linspace(dfGroup['Year'].min(), dfGroup['Year'].max(), 500)
Y_ = X_Y_Spline(X_)

# Plot the data
a4_dims = (15, 10)
fig, ax1 = plt.subplots(figsize=a4_dims)
sns.barplot(x="Year", y="Total Deaths",
            data=dfGroup, color='#42b7bd', label='Barplot label', ax=ax1)
x_plot = np.linspace(0, len(dfGroup) - 1, len(X_))
sns.lineplot(x=x_plot, y=Y_, marker='o', label='LinePlot label', ax=ax1)
ax1.set_ylim(ymin=0) # let bars touch the bottom of the plot
ax1.margins(x=0.02) # less margins left and right
# ax1.legend(title='legend title') # optionally change the legend
plt.show()

PS：如果 ax 已经创建，它应该作为 seaborn 的 axes-level functions 的参数提供（所以，sns.barplot(..., ax=ax1) 而不是 ax1 = sns.barplot(...)。

【讨论】：